Hugging Face is hiring a
On-device ML Engineer

Summary

Hugging Face is seeking an experienced Swift Developer and Machine Learning enthusiast to join their team as an On-device ML Engineer. The role involves optimizing, quantizing, and converting models for efficient execution on iPhones and Macs using technologies like Core ML and MLX. The engineer will also contribute to open source projects and create tools to make it easier for developers to distribute models in device-friendly formats.

Requirements

• Strong background in Swift development with a practical, builder mindset and good sense of software and application design
• Deep understanding of essential model architectures and passion for machine learning
• Experience using Core ML and understanding its advantages and limitations
• Eagerness to publish and contribute to open-source libraries to help developers adopt ML
• Versatility to move across different levels of abstraction as needed, from UI to Metal kernels
• Understanding of various optimization techniques, such as kv-caching in transformers and post-training quantization
• Strong systems understanding to identify performance bottlenecks
• Experience with various frameworks like llama.cpp, MLX, PyTorch, and CoreNet

Responsibilities

• Optimize, quantize, and convert the best models for efficient execution on iPhones and Macs
• Design, build, and contribute to open source software that demonstrates model usage and develop libraries to minimize friction for developers
• Write Swift code to implement or optimize ML tasks, including pre-and post-processing pipelines
• Produce high-quality technical documentation, such as blog posts, tutorials, guides, social media threads, and concise demo apps

Benefits

• Flexible working hours and remote options
• Health, dental, and vision benefits for employees and their dependents
• Parental leave and flexible paid time off